Hande KÜÇÜKÖNDER, Kubilay Kazım VURSAVUŞ, Zehan KESİLMİŞ

Mekanik hasarsız çarpma tekniğiyle domatesin sertliğine göre sınıfandırılması

Bu çalışmada, mekanik hasarsız çarpma tekniği kullanılarak domatesin sertliklerine göre sınıfandırılması incelenmiştir.Denemelerde Bandita F1 domates çeşidi kullanılmıştır. Düşük çarpma enerjili yanal çarpma aygıtı kullanılarak yapılanhasarsız çarpma ölçümlerinde, çarpma ivmesi ve temas zamanı, çarpma başlığı üzerine yerleştirilmiş ivme algılayıcıile algılanmış ve ana çarpma parametreleri (maksimum çarpma ivmesi, maksimum çarpma ivmesinde ölçülen zamanve temas zamanı) elde edilen eğrilerden bulunmuştur. Diğer çarpma parametreleri ana parametrelerden ve elastisiteteorisinden türetilmiştir. Bu hasarsız çarpma parametreleri, hasarlı referans parametresi ile karşılaştırılmıştır. Hasarlıreferans parametresi ölçümlerinde, kabuk yırtılma noktasındaki kuvvet-deformasyon oranı kullanılmış ve bu değerdomates sertliği olarak ifade edilmiştir. Domateslerin sertlik gruplandırmalarında kümeleme analizi kullanılmıştır.Ayrıca, domateslerin sınıfandırma işlemlerinde, sahip oldukları sertlik gruplarındaki hatalı sınıfandırma olasılığınıminimize edecek hasarsız çarpma parametrelerinin optimum doğrusal kombinasyonlarını bulmak için, doğrusal ayırmaanalizi kullanılmıştır. Sınıfandırma hassasiyeti doğrusal ayırma analizi ile iyileştirilmiş ve işlenen parametre sayısıstepwise regresyon analizi ile azaltılmıştır. İstatistiksel analiz sonuçları, hasarlı referans ve hasarsız çarpma parametreleriarasındaki korelasyonun önemli olduğunu göstermiştir. Doğrusal ayırma analizi sonuçlarına göre, doğrusal sınıfandırmahassasiyeti ana çarpma parametreleri yaklaşımı için % 77.27 ve on çarpma parametre yaklaşımı için de % 81.82 olarakbulunmuştur. Ayrıca, stepwise regresyon analizi ile belirlenmiş olan en önemli üç çarpma parametresi kullanılarakyapılan doğrusal ayırma analizi sonuçları, domateslerin doğru sınıfandırma hassasiyetinin % 82.96ya yükseltildiğinigöstermiştir. Sonuç olarak, statik koşullarda test edilmiş olan mekanik hasarsız çarpma test cihazı domates için yükseksınıfandırma hassasiyeti sonuçları vermiştir. Bu performans, mekanik hasarsız çarpma tekniğinin, domateslerinelektronik sınıfandırma hattında gerçek zamanlı sertlik sınıfandırma amaçlı kullanılabileceğini göstermektedir.

Firmness classifcation of tomato by mechanical nondestructive impact technique

In this study, frmness classifcation of tomato was aimed by using mechanical nondestructive impact technique. BanditaF1 tomato variety was used during the tests. In the nondestructive impact measurements done by lateral impactor withlow impact energy, impact acceleration and contact time were sensed by an accelerometer attached on impact head,and main impact parameters (maximum impact acceleration, time required to reach maximum acceleration and contacttime) were extracted from the curve. Other impact parameters were derived from the main impact parameters and theoryof elasticity. These nondestructive impact parameters were compared with destructive reference parameters. Force-deformation ratio at rupture point was used in the measurements of destructive reference parameter and this was expressedto be tomato frmness. Cluster analysis was used for frmness groups of tomatoes. Furthermore, linear discriminatinganalysis was used to fnd an optimum linear combination of the impact parameters that minimizes the probability ofmisclassifying tomatoes into their respective groups for frmness classifcation procedure of tomatoes. The accuracyof classifcation was improved with linear discriminating analysis, and the number of parameters being processedwas reduced with stepwise regression analysis. Statistical analysis showed that the correlations between destructivereference and nondestructive impact parameters were signifcant. According to the results of linear discriminatinganalysis, accuracy of the best classifcation for main impact parameter approach and all ten impact parameters approachwas found to be 77.27% and 81.82%, respectively. Furthermore, linear discriminating analysis results for three mostimportant impact parameters obtained with stepwise regression analysis showed that accuracy of the best classifcationof tomatoes was improved to 82.96%. As a result, mechanical nondestructive test device tested in static conditions gavehigh accuracy of classifcation for tomato. This performance shows that mechanical nondestructive impact techniquecould be used for real-time frmness classifcation of tomatoes in the electronic sorting line.

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